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Significant problems facing all experimental and computational sciences arise from growing data size and complexity. Common to all these problems is the need to perform efficient data I/O on diverse computer architectures. In our scientific application, the largest parallel particle simulations generate vast quantities of six-dimensional data. Such a simulation run produces data for an aggregate data size up to several TB per run. Motived by the need to address data I/O and access challenges, we have implemented H5Part, an open source data I/O API that simplifies the use of the Hierarchical Data Format v5 library (HDF5). HDF5 is an industry standard for high performance, cross- platform data storage and retrieval that runs on all contemporary architectures from large parallel supercomputers to laptops. H5Part, which is oriented to the needs of the particle physics and cosmology communities, provides support for parallel storage and retrieval of particles, structured and in the future unstructured meshes. In this paper, we describe recent work focusing on I/O support for particles and structured meshes and provide data showing performance on modern supercomputer architectures like the IBM POWER 5.